OpenAI’s data, particularly for training large models like GPT-3 and GPT-4, comes from a variety of publicly available and licensed sources. Here’s a breakdown of the key sources OpenAI uses for training its language models:
1. Public Web DataWeb Crawls: OpenAI uses a wide range of publicly available web pages, which include websites, blogs, forums, news articles, and other textual content freely available on the internet. Books and Articles: Content from publicly available books, research papers, articles, and other publications. Wikipedia: Wikipedia’s vast amount of knowledge across different topics is often a key resource. Forums and Social Media: While OpenAI may use data from platforms like Reddit or StackExchange (among others), it's important to note that any data derived from these platforms is typically aggregated and anonymized. 2. Licensed Data
OpenAI may also have access to proprietary data through licensing agreements with certain organizations, such as:
News sources: Subscription-based news websites or archives, which provide high-quality content for training. Research Papers: Databases like arXiv or academic publishers where papers are publicly available or licensed for use. 3. Books and Academic Journals OpenAI uses a large corpus of books and academic papers across various domains to give the model a broad knowledge base, particularly in specialized fields like science, technology, literature, history, and more. 4. Code and Programming Resources Models like GPT-4 have been trained on a large corpus of code from open-source platforms like GitHub to better understand and generate code across a variety of programming languages. 5. Other Datasets
OpenAI uses a range of curated datasets, such as:
Common Crawl: A massive dataset of web data scraped regularly. Project Gutenberg: A collection of free eBooks, especially classic literature. Open Subtitles: Text data from movie subtitles, which help improve conversational understanding.
OpenAI’s data, particularly for training large models like GPT-3 and GPT-4, comes from a variety of publicly available and licensed sources. Here’s a breakdown of the key sources OpenAI uses for training its language models:
1. Public Web Data Web Crawls: OpenAI uses a wide range of publicly available web pages, which include websites, blogs, forums, news articles, and other textual content freely available on the internet. Books and Articles: Content from publicly available books, research papers, articles, and other publications. Wikipedia: Wikipedia’s vast amount of knowledge across different topics is often a key resource. Forums and Social Media: While OpenAI may use data from platforms like Reddit or StackExchange (among others), it's important to note that any data derived from these platforms is typically aggregated and anonymized. 2. Licensed DataOpenAI may also have access to proprietary data through licensing agreements with certain organizations, such as:
News sources: Subscription-based news websites or archives, which provide high-quality content for training. Research Papers: Databases like arXiv or academic publishers where papers are publicly available or licensed for use. 3. Books and Academic Journals OpenAI uses a large corpus of books and academic papers across various domains to give the model a broad knowledge base, particularly in specialized fields like science, technology, literature, history, and more. 4. Code and Programming Resources Models like GPT-4 have been trained on a large corpus of code from open-source platforms like GitHub to better understand and generate code across a variety of programming languages. 5. Other DatasetsOpenAI uses a range of curated datasets, such as:
Common Crawl: A massive dataset of web data scraped regularly. Project Gutenberg: A collection of free eBooks, especially classic literature. Open Subtitles: Text data from movie subtitles, which help improve conversational understanding.啊哈哈哈。。。。。。。。。。。
书和报纸，本来就是让人来读的。
别人的作业，是私密的，未经容许，是偷看。
啊哈哈哈。。。。。。。。。。
啊哈哈哈。。。。。。。。。。。
到底是谁没完没了？
啊哈哈哈。。。。。。。。。。。。。。
我们一边看戏一边评论，不行么？
啊哈哈哈。。。。。。。。。。
维基百科：维基百科的数据是开放和免费的，任何人都可以访问并使用其内容（依据CC BY-SA 许可协议），这使得维基百科成为一个非常宝贵的知识资源，OpenAI 可能会将它作为一个训练数据源。因为维基百科的内容是公共领域的，所以 OpenAI 无需支付费用就可以利用它。
开放数据集：OpenAI 使用了很多公共数据集（如 Common Crawl、Project Gutenberg 等）作为训练数据。这些数据集也是公开的，OpenAI 可以免费访问并使用它们。
之前，外面已经讨论剽窃的事好几个小时了！
不要做鸵鸟好不好？
啊哈哈哈。。。。。。。。。。。。。
DS是原创，还是抄OpenAI作业?